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Graphical and numerical diagnostic tools to assess suitability of multiple imputations and imputation models
dc.contributor.authorBondarenko, Irina
dc.contributor.authorRaghunathan, Trivellore
dc.date.accessioned2016-07-06T18:21:16Z
dc.date.available2017-09-06T14:20:20Zen
dc.date.issued2016-07-30
dc.identifier.citationBondarenko, Irina; Raghunathan, Trivellore (2016). "Graphical and numerical diagnostic tools to assess suitability of multiple imputations and imputation models." Statistics in Medicine 35(17): 3007-3020.
dc.identifier.issn0277-6715
dc.identifier.issn1097-0258
dc.identifier.urihttps://hdl.handle.net/2027.42/122409
dc.publisherWiley
dc.subject.otherdiagnostics
dc.subject.othermultiple imputation
dc.subject.otherpropensity score
dc.subject.othercongeniality
dc.titleGraphical and numerical diagnostic tools to assess suitability of multiple imputations and imputation models
dc.typeArticleen_US
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelStatistics and Numeric Data
dc.subject.hlbsecondlevelPublic Health
dc.subject.hlbsecondlevelMedicine (General)
dc.subject.hlbsecondlevelStatistics and Numeric Data
dc.subject.hlbsecondlevelPublic Health
dc.subject.hlbsecondlevelMedicine (General)
dc.subject.hlbtoplevelScience
dc.subject.hlbtoplevelSocial Sciences
dc.subject.hlbtoplevelHealth Sciences
dc.subject.hlbtoplevelScience
dc.subject.hlbtoplevelSocial Sciences
dc.subject.hlbtoplevelHealth Sciences
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/122409/1/sim6926_am.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/122409/2/sim6926.pdf
dc.identifier.doi10.1002/sim.6926
dc.identifier.sourceStatistics in Medicine
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dc.owningcollnameInterdisciplinary and Peer-Reviewed


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